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Lecture 16: Genomic data in R

This lecture will unite the last lecture's content on genomic analysis with our previous coding in R. The packages we'll use this week are from Bioconductor, a collection of software specifically designed for genomic analysis in R.

Lecture Notes

Lecture slides

Learning objectives

  • Use Bioconductor packages to work with genomic data in R
  • Load, inspect, and query genomic data (BED/SEG, BAM, VCF files)
  • Identify and annotate genomic variants

Before the class

We will be working through some tutorials directly on your laptop using R Studio.

1. Install the R packages

  • Tutorial is tested for R-4.0.3
  • You should run this script in RStudio to ensure all Bioconductor packages are installed.
  • This script will install the following packages:
    • Rsamtools: querying BAM files
    • VariantAnnotation: reading VCF files
    • GenomicRanges: manipulating genomic data

2. Class materials: R Markdown files containing the tutorials

  • If you have not done so already, update your local copy of the class repository from GitHub. You should have a directory (lecture16) containing the following three RMarkdown tutorials:

3. Class materials: Genomic and sequencing data for the tutorials

  • Please download all data files found in this folder and add them to your lecture16 directory. The files should have the following filenames:
    • BRCA.genome_wide_snp_6_broad_Level_3_scna.seg
    • BRCA_IDC_cfDNA.bam
    • BRCA_IDC_cfDNA.bam.bai
    • GIAB_highconf_v.3.3.2.vcf.gz (if this file was automatically uncompressed on your computer, resulting in a file named GIAB_highconf_v.3.3.2.vcf, look in your Trash folder to find the original file ending in gz)
    • GIAB_highconf_v.3.3.2.vcf.gz.tbi